Triple

T20881962
Position Surface form Disambiguated ID Type / Status
Subject Telefon E514173 entity
Predicate basedOnWorkAuthor P2806 FINISHED
Object Walter Wager NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Walter Wager | Statement: [Telefon, basedOnWorkAuthor, Walter Wager]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Wager
Context triple: [Telefon, basedOnWorkAuthor, Walter Wager]
  • A. Walter Wager chosen
    Walter Wager was an American novelist best known for his suspense and espionage thrillers, one of which inspired the film "Die Hard 2."
  • B. Walter Wyman
    Walter Wyman was an American engineer and power company executive known for his pioneering role in developing hydroelectric power projects in Maine.
  • C. Walter Gilman
    Walter Gilman is the ill-fated Miskatonic University student whose occult studies and nightmarish experiences drive the plot of H. P. Lovecraft’s horror story "The Dreams in the Witch House."
  • D. Walter J. Mercer
    Walter J. Mercer was the discoverer and namesake of Mercer Caverns, a notable limestone cave in California.
  • E. Walter Parratt
    Walter Parratt was a prominent English organist, composer, and teacher who served as Master of the Queen’s (later King’s) Music in the late 19th and early 20th centuries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c67a33548190b0f5ba58b001d387 completed April 21, 2026, 12:36 a.m.
Created at: April 16, 2026, 12:46 p.m.